Data Platform Developer

• Strong hands-on experience with Snowflake, PySpark, Python, and SQL.
• Expertise in designing and developing scalable ETL/ELT pipelines for large-volume datasets.
• Experience with data ingestion, transformation, data quality, reconciliation, and performance optimization.
• Strong understanding of dimensional modeling, data warehousing concepts, and metadata-driven frameworks.

Cloud & Big Data

• Hands-on experience with AWS services such as S3, Glue, Lambda, EMR, Athena, Redshift, ECS/EKS, and IAM.
• Experience building cloud-native data solutions and modern data platforms.
• Strong understanding of distributed processing and big data architectures.

Snowflake

• Expertise in Snowflake architecture, SnowSQL, Streams, Tasks, Dynamic Tables, Snowpark, Data Sharing, and Performance Tuning.
• Experience implementing scalable data marts, semantic layers, and enterprise reporting solutions.
• Knowledge of Snowflake security, governance, and cost optimization best practices.

AI & Emerging Technologies

• Exposure to Generative AI, Agentic AI, LLMs, Vector Databases, and AI-powered analytics solutions.
• Experience leveraging AI services for data discovery, data quality, metadata management, or business insights.
• Understanding of RAG architectures, embeddings, and AI-assisted data engineering workflows.

DevOps & Automation

• Experience with Git, Jenkins, GitHub Actions, Terraform, and Infrastructure as Code.
• Familiarity with CI/CD pipelines and automated deployment of data workloads.
• Experience with workflow orchestration tools such as Airflow or similar platforms.

Data Integration

• Experience integrating data from relational databases, APIs, event streams, and enterprise applications.
• Exposure to CDC, real-time processing, Kafka, and event-driven architectures.
  • Strong understanding of data lineage, governance, retention, and regulatory compliance requirements.